Monitoring global deforestation can be a tedious process of analyzing individual satellite images from a handful of government spacecraft and trying to infer trends from relatively blurry pixels. Even so, recent advances have yielded clues about shifting hotspots of deforestation, including tropical nations and industrialized countries.

The mini-boom in the private sector satellite and satellite data processing industries, however, may soon yield a dramatically different deforestation monitoring regime. In fact, it may soon be possible to predict where deforestation is about to occur, according to James Crawford, founder of Orbital Insight, a Silicon Valley company that uses a technique called deep learning to analyze massive data sets.

Screenshot of Global Forest Watch, showing it detected deforestation from major tornadoes in Alabama in 2011 (two pink lines).

Image: Global Forest Watch

Between 2000 and 2012, the world lost 2.3 million square kilometers of tree cover, or about 888,000 square miles — the equivalent of losing 50 soccer fields’ worth of forests every minute of every day, WRI says. Forests are reservoirs of biodiversity, particularly tropical rainforests, and they are also valuable storage areas for carbon. When trees are chopped down, long-stored carbon is released into the atmosphere, adding to manmade global warming.

According to recently released data from Global Forest Watch, Russia and Canada topped the list of countries with the most tree cover loss, mainly due to forest fires, jointly accounting for 34% of total loss. (Tree cover loss is a measure of the total loss of all trees within a specific area regardless of the cause.) The data show that Russia, Canada, Brazil, the United States and Indonesia make up the top five countries for average annual tree cover loss from 2011 to 2013.

Predicting deforestation before it occurs

Detecting deforestation has "always been an inherently reactive approach," James Anderson, who works on forest issues for WRI, told Mashable. “What Orbital Insight and Global Forest Watch are going to do is to try to be more proactive.”

Aaron Steele, chief technology officer at WRI, told Mashable that artificial intelligence approaches to sifting through huge datasets will be "really key in this space in the next five or 10 years.

“As we get more and more data about the world, processing it in real-time is going to be the challenge,” he said. Eventually, he says, “we want to take that to the next level and start to build systems that can automate decision making.”

Under the partnership, Orbital Insight will analyze high resolution satellite images of tens of millions of acres of forest to discover patterns that identify indicators of deforestation risk, such as the building of new roads into sections of tropical rainforests.

Deep learning is a form of artificial intelligence that involves processing huge quantities of data to solve problems, according to a press release. Jeff Stein, vice president of business development at Orbital Insight, told Mashable that the company has built a generic software system that can be applied to many different questions, teaching itself through data processing. Detecting and predicting deforestation will require the development of algorithms, but basically comes down to “pointing the toolset at this particular problem,” he said.

“There is going to be some research and development here, it’s not right off the shelf.”

The technology will also increase transparency around the impact of global commodity supply chains on forest loss. So-called “forest-risk commodities” such as palm oil, beef, soy, pulp and paper has led to over 70% of deforestation in tropical forests, often illegally, according to a press release.

“We currently know a lot about forest clearing that has happened in the past, but soon we will have the power to look ahead and identify the forest areas at greatest risk,” Steele, WRI's CTO, said.

Global Forest Watch was launched in 2014 and provides online forest monitoring and deforestation alert capabilities through a range of partners, from Google to the University of Maryland and NASA. For data released earlier in April, Global Forest Watch's partners analyzed 400,000 images from NASA's Landsat satellite.

However, the alerts are not yet particularly useful for, say, park managers, since they are only told which parts of a forest were chopped down, perhaps illegally, rather than being able to go out and prevent illegal deforestation.

Image of Brazil taken April 2, 2015, from a Planet Labs satellite.

Image: Planet Labs

“There’s still a sign gap if you’re a decision maker, between getting an alert and being able to respond,” Anderson says.

Until now, Global Forest Watch has mainly relied on data from Digital Globe and NASA's Landsat program, but both WRI and Orbital Insight told Mashable that they intend to try to plug in data from forthcoming constellations of smaller, more numerous commercial satellites from Google's SkyBox offshoot, as well as Planet Labs and other similar companies.

Crawford, Orbital Insight's founder who previously led the Google Books project, says the limiting factor for data coming from many government satellites is their relatively low-resolution. This makes the commercial sector's advances particularly intriguing for forestry work. “There’s some big advantages in going to a higher resolution," he said. "You can start to see things like road going to a forest before the forest is cut down."

In fact, Orbital Insight is dependent on companies like Planet Labs for its work, since as Crawford put it, “Our whole company is based on the premise that we want to process satellite imagery at the very large scale.”

Mashable
is a global, multi-platform media and entertainment company. Powered by its own proprietary technology, Mashable is the go-to source for tech, digital culture and entertainment content for its dedicated and influential audience around the globe.